IDEAS home Printed from https://ideas.repec.org/p/tul/wpaper/2512.html

The "Missing Rich" in Household Surveys: Causes and Correction Approaches Extended Version with Technical Appendixes

Author

Listed:
  • Nora Lustig

    (Tulane University)

  • Andrea Vigorito

    (Universidad de la Republica, Uruguay)

Abstract

Inequality measures based on household surveys may be biased because they fail to capture the upper tail of the income distribution properly. The "missing rich" problem stems from sampling errors, item and unit nonresponse, underreporting of income, and data preprocessing techniques like top coding. This paper reviews salient approaches to address the underrepresentation of the rich in household surveys. Approaches are classified based on information sources and method. In terms of information sources, the distinction is between within-survey data and survey data combined with external sources (e.g., tax records). In terms of methods, we identify three categories: replacing, reweighting, and combined reweighting and replacing. We show that income inequality levels and trends are sensitive to the correction approach. This paper is a companion piece to the chapter of the same name and includes all the appendices that could not be incorporated into the chapter due to space limitations.

Suggested Citation

  • Nora Lustig & Andrea Vigorito, 2025. "The "Missing Rich" in Household Surveys: Causes and Correction Approaches Extended Version with Technical Appendixes," Working Papers 2512, Tulane University, Department of Economics.
    • Handle: RePEc:tul:wpaper:2512
    as

    Download full text from publisher

    File URL: http://repec.tulane.edu/RePEc/pdf/tul2512.pdf
    File Function: First Version, December 2025
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jenkins, Stephen P. & Rios-Avila, Fernando, 2020. "Modelling errors in survey and administrative data on employment earnings: Sensitivity to the fraction assumed to have error-free earnings," Economics Letters, Elsevier, vol. 192(C).
    2. Raj Chetty & John N Friedman & Michael Stepner & Opportunity Insights Team & Camille Baker & Harvey Barnhard & Matt Bell & Gregory Bruich & Tina Chelidze & Lucas Chu & Westley Cineus & Sebi Devlin-Fol, 2024. "The Economic Impacts of COVID-19: Evidence from a New Public Database Built Using Private Sector Data," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 139(2), pages 829-889.
    3. Bruce D. Meyer & Nikolas Mittag, 2019. "Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness, and Holes in the Safety Net," American Economic Journal: Applied Economics, American Economic Association, vol. 11(2), pages 176-204, April.
    4. Angus Deaton, 2005. "ERRATUM: Measuring Poverty in a Growing World (or Measuring Growth in a Poor World)," The Review of Economics and Statistics, MIT Press, vol. 87(2), pages 395-395, May.
    5. Lillard, Lee & Smith, James P & Welch, Finis, 1986. "What Do We Really Know about Wages? The Importance of Nonreporting and Census Imputation," Journal of Political Economy, University of Chicago Press, vol. 94(3), pages 489-506, June.
    6. VAN KERM Philippe, 2007. "Extreme incomes and the estimation of poverty and inequality indicators from EU-SILC," IRISS Working Paper Series 2007-01, IRISS at CEPS/INSTEAD.
    7. Bruce D. Meyer & Wallace K. C. Mok & James X. Sullivan, 2015. "Household Surveys in Crisis," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 199-226, Fall.
    8. John M. Abowd & Martha H. Stinson, 2013. "Estimating Measurement Error in Annual Job Earnings: A Comparison of Survey and Administrative Data," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1451-1467, December.
    9. Chancel, Lucas & Cogneau, Denis & Gethin, Amory & Myczkowski, Alix & Robilliard, Anne-Sophie, 2023. "Income inequality in Africa, 1990–2019: Measurement, patterns, determinants," World Development, Elsevier, vol. 163(C).
    10. Stephen P. Jenkins, 2017. "Pareto Models, Top Incomes and Recent Trends in UK Income Inequality," Economica, London School of Economics and Political Science, vol. 84(334), pages 261-289, April.
    11. Facundo Alvaredo, 2007. "The Rich in Argentina over the twentieth century: From the Conservative Republic to the Peronist experience and beyond 1932-2004," Working Papers halshs-00588318, HAL.
    12. Dean R. Hyslop & Wilbur Townsend, 2020. "Earnings Dynamics and Measurement Error in Matched Survey and Administrative Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 457-469, April.
    13. Anda DAVID & Rocco ZIZZAMIA & Murray LEIBBRANDT, 2021. "Inequality in sub-Saharan Africa: A Review Paper," Working Paper 790e79ea-8499-4760-a555-6, Agence française de développement.
    14. Vladimir Hlasny & Paolo Verme, 2018. "Top Incomes and the Measurement of Inequality in Egypt," The World Bank Economic Review, World Bank, vol. 32(2), pages 428-455.
    15. Facundo Alvaredo, 2007. "The Rich in Argentina over the twentieth century: From the Conservative Republic to the Peronist experience and beyond 1932-2004," PSE Working Papers halshs-00588318, HAL.
    16. Stefan Bach & Martin Beznoska & Viktor Steiner, 2016. "Who Bears the Tax Burden in Germany? Tax Structure Slightly Progressive," DIW Economic Bulletin, DIW Berlin, German Institute for Economic Research, vol. 6(51/52), pages 601-608.
    17. Thomas Piketty & Li Yang & Gabriel Zucman, 2019. "Capital Accumulation, Private Property, and Rising Inequality in China, 1978–2015," American Economic Review, American Economic Association, vol. 109(7), pages 2469-2496, July.
    18. Christopher R. Bollinger & Barry T. Hirsch, 2006. "Match Bias from Earnings Imputation in the Current Population Survey: The Case of Imperfect Matching," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 483-520, July.
    19. Anthony Atkinson & Thomas Piketty, 2010. "Top Incomes : A Global Perspective," PSE-Ecole d'économie de Paris (Postprint) halshs-00754875, HAL.
    20. Marcelo Medeiros & Juliana Castro Galvão & Luísa Azevedo Nazareno, 2018. "Correcting the Underestimation of Top Incomes: Combining Data from Income Tax Reports and the Brazilian 2010 Census," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 233-244, January.
    21. Cowell, Frank A. & Flachaire, Emmanuel, 2007. "Income distribution and inequality measurement: The problem of extreme values," Journal of Econometrics, Elsevier, vol. 141(2), pages 1044-1072, December.
    22. Stephen P. Jenkins & Richard V. Burkhauser & Shuaizhang Feng & Jeff Larrimore, 2011. "Measuring inequality using censored data: a multiple‐imputation approach to estimation and inference," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(1), pages 63-81, January.
    23. Christoph Lakner & Branko Milanovic, 2016. "Global Income Distribution: From the Fall of the Berlin Wall to the Great Recession," The World Bank Economic Review, World Bank, vol. 30(2), pages 203-232.
    24. Roy van der Weide & Christoph Lakner & Elena Ianchovichina, 2018. "Is Inequality Underestimated in Egypt? Evidence from House Prices," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 64(s1), pages 55-79, October.
    25. Peter Valet & Jule Adriaans & Stefan Liebig, 2019. "Comparing survey data and administrative records on gross earnings: nonreporting, misreporting, interviewer presence and earnings inequality," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(1), pages 471-491, January.
    26. Anthony Atkinson & Thomas Piketty, 2007. "Top incomes over the twentieth century: A contrast between continental european and english-speaking countries," Post-Print halshs-00754859, HAL.
    27. Miguel SzEkely & Marianne Hilgert, 2007. "What's Behind the Inequality We Measure? An Investigation Using Latin American Data," Oxford Development Studies, Taylor & Francis Journals, vol. 35(2), pages 197-217.
    28. Thomas Blanchet & Ignacio Flores & Marc Morgan, 2022. "The weight of the rich: improving surveys using tax data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 119-150, March.
    29. Atkinson, A. B. & Piketty, Thomas (ed.), 2010. "Top Incomes: A Global Perspective," OUP Catalogue, Oxford University Press, number 9780199286898.
    30. Oscar Altimir, 1987. "Income Distribution Statistics In Latin America And Their Reliability," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 33(2), pages 111-155, June.
    31. Martin Ravallion, 2022. "Missing Top Income Recipients," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 205-222, March.
    32. François Bourguignon, 2018. "Simple adjustments of observed distributions for missing income and missing people," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(2), pages 171-188, June.
    33. Emmanuel Flachaire & Nora Lustig & Andrea Vigorito, 2023. "Underreporting of Top Incomes and Inequality: A Comparison of Correction Methods using Simulations and Linked Survey and Tax Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(4), pages 1033-1059, December.
    34. Burkhauser, Richard V. & Feng, Shuaizhang & Larrimore, Jeff, 2010. "Improving imputations of top incomes in the public-use current population survey by using both cell-means and variances," Economics Letters, Elsevier, vol. 108(1), pages 69-72, July.
    35. Korinek, Anton & Mistiaen, Johan A. & Ravallion, Martin, 2007. "An econometric method of correcting for unit nonresponse bias in surveys," Journal of Econometrics, Elsevier, vol. 136(1), pages 213-235, January.
    36. Richard V. Burkhauser & Nicolas Hérault & Stephen P. Jenkins & Roger Wilkins, 2018. "Survey Under‐Coverage of Top Incomes and Estimation of Inequality: What is the Role of the UK's SPI Adjustment?," Fiscal Studies, John Wiley & Sons, vol. 39(2), pages 213-240, June.
    37. Alvaredo, Facundo, 2011. "A note on the relationship between top income shares and the Gini coefficient," Economics Letters, Elsevier, vol. 110(3), pages 274-277, March.
    38. Stefan Bach & Giacomo Corneo & Viktor Steiner, 2009. "From Bottom To Top: The Entire Income Distribution In Germany, 1992–2003," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 55(2), pages 303-330, June.
    39. Andreas Alfons & Matthias Templ & Peter Filzmoser, 2013. "Robust estimation of economic indicators from survey samples based on Pareto tail modelling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(2), pages 271-286, March.
    40. Stefan Angel & Franziska Disslbacher & Stefan Humer & Matthias Schnetzer, 2019. "What did you really earn last year?: explaining measurement error in survey income data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(4), pages 1411-1437, October.
    41. Christopher R. Bollinger & Barry T. Hirsch & Charles M. Hokayem & James P. Ziliak, 2019. "Trouble in the Tails? What We Know about Earnings Nonresponse 30 Years after Lillard, Smith, and Welch," Journal of Political Economy, University of Chicago Press, vol. 127(5), pages 2143-2185.
    42. Anton Korinek & Johan Mistiaen & Martin Ravallion, 2006. "Survey nonresponse and the distribution of income," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 4(1), pages 33-55, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lustig, Nora & Vigorito, Andrea, 2025. "The “Missing Rich” in Household Surveys: Causes and Correction Approaches," SocArXiv 97ng6_v1, Center for Open Science.
    2. Katy Bergstrom & William Dodds & Nicholas Lacoste & Juan Rios, 2025. "Estimating the Welfare Cost of Labor Supply Frictions," Working Papers 2503, Tulane University, Department of Economics.
    3. Ferreira, Francisco H. G. & Brunori, Paolo, 2024. "Inherited inequality, meritocracy, and the purpose of economic growth," LSE Research Online Documents on Economics 126263, London School of Economics and Political Science, LSE Library.
    4. Nora Lustig, 2019. "The “Missing Rich” in Household Surveys: Causes and Correction Approaches," Commitment to Equity (CEQ) Working Paper Series 75, Tulane University, Department of Economics.
    5. repec:osf:socarx:j23pn_v1 is not listed on IDEAS
    6. Emmanuel Flachaire & Nora Lustig & Andrea Vigorito, 2023. "Underreporting of Top Incomes and Inequality: A Comparison of Correction Methods using Simulations and Linked Survey and Tax Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(4), pages 1033-1059, December.
    7. Nora Lustig, 2018. "Measuring the Distribution of Household Income, Consumption and Wealth: State of Play and Measurement Challenges," Working Papers 1801, Tulane University, Department of Economics.
    8. Bartels, Charlotte & Waldenström, Daniel, 2021. "Inequality and top incomes," GLO Discussion Paper Series 959, Global Labor Organization (GLO).
    9. Mathias Silva, 2023. "Parametric models of income distributions integrating misreporting and non-response mechanisms," AMSE Working Papers 2311, Aix-Marseille School of Economics, France.
    10. Vladimir Hlasny & Paolo Verme, 2022. "The Impact of Top Incomes Biases on the Measurement of Inequality in the United States," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 749-788, August.
    11. Diego Winkelried & Bruno Escobar, 2022. "Declining inequality in Latin America? Robustness checks for Peru," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 223-243, March.
    12. Rafael Carranza & Marc Morgan & Brian Nolan, 2023. "Top Income Adjustments and Inequality: An Investigation of the EU‐SILC," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(3), pages 725-754, September.
    13. Kerr,Andrew Nicholas & Zondi,Mxolisi, 2024. "Measuring the Upper Tail of the Income and Wealth Distributions," Policy Research Working Paper Series 10836, The World Bank.
    14. Marko Ledić & Ivica Rubil & Ivica Urban, 2024. "Using tax records to correct for under‐representation of top income sources in surveys," Fiscal Studies, John Wiley & Sons, vol. 45(4), pages 521-541, December.
    15. Vladimir Hlasny & Paolo Verme, 2018. "Top Incomes and Inequality Measurement: A Comparative Analysis of Correction Methods Using the EU SILC Data," Econometrics, MDPI, vol. 6(2), pages 1-21, June.
    16. Frank Cowell & Emmanuel Flachaire, 2021. "Inequality Measurement: Methods and Data," Post-Print hal-03589066, HAL.
    17. Lidia Ceriani & Paolo Verme, 2022. "Population Changes and the Measurement of Inequality," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 162(2), pages 549-575, July.
    18. Tahnee Christelle Ooms, 2021. "Correcting the Underestimation of Capital Incomes in Inequality Indicators: with an Application to the UK, 1997–2016," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(3), pages 929-953, October.
    19. Thomas Blanchet & Ignacio Flores & Marc Morgan, 2022. "The weight of the rich: improving surveys using tax data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 119-150, March.
    20. Vladimir Hlasny, 2021. "Parametric representation of the top of income distributions: Options, historical evidence, and model selection," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1217-1256, September.
    21. Xavier Jara & Nicolás Oliva, 2018. "Top income adjustments and tax reforms in Ecuador," WIDER Working Paper Series wp-2018-165, World Institute for Development Economic Research (UNU-WIDER).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tul:wpaper:2512. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Nicholas Lacoste (email available below). General contact details of provider: https://edirc.repec.org/data/detulus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.